A benchmark image dataset for industrial tools

Cai Luo, Leijian Yu, Erfu Yang, Huiyu Zhou, Peng Ren

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Robots and Artificial Intelligence (AI) play an increasingly important role in manufacture. One of the tasks is to identify tools in the scene so that the tools can be applied to different assembly purposes. In the AI community, many datasets have been generated and deployed to train robots to recognize individual items, however, these datasets are scene-specific and lack generic background. In this paper, we report our dataset contains photos of 8 objects types that would be easily recognized by qualified workers. This is achieved by gathering images of common tools in a typical factory. The ground truth categories of our dataset are manually labeled by experienced workers, which would be worthy evaluation tools for the intelligence industrial systems. The equipment used and the image collection process are discussed, along with the data format. The mean average precisions range from 64.37% to 78.20%, which bring the possibility for future improvement. The dataset is ideal to evaluate and benchmark view-point variant, vision-based control algorithm for industry robots. It is now public available from
LanguageEnglish
Pages341-348
Number of pages8
JournalPattern Recognition Letters
Volume125
Early online date17 May 2019
DOIs
Publication statusPublished - 1 Jul 2019

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Robots
Artificial intelligence
Industrial plants
Industry

Keywords

  • benchmark
  • industrial tools
  • image dataset

Cite this

Luo, Cai ; Yu, Leijian ; Yang, Erfu ; Zhou, Huiyu ; Ren, Peng. / A benchmark image dataset for industrial tools. In: Pattern Recognition Letters. 2019 ; Vol. 125. pp. 341-348.
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A benchmark image dataset for industrial tools. / Luo, Cai; Yu, Leijian; Yang, Erfu; Zhou, Huiyu; Ren, Peng.

In: Pattern Recognition Letters, Vol. 125, 01.07.2019, p. 341-348.

Research output: Contribution to journalArticle

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